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<meta name="title" content="A Low-Carbohydrate Ketogenic Diet and Treadmill Training Enhanced Fatty Acid Oxidation Capacity but Did Not Enhance Maximal Exercise Capacity in Mice">
<meta name="description" content="The low-carbohydrate ketogenic diet (LCKD) is a dietary approach characterized by the intake of high amounts of fat, a balanced amount of protein, and low carbohydrates, which is insufficient for metabolic demands. Previous studies have shown that an LCKD alone may contribute to fatty acid oxidation capacity, along with endurance. In the present study, we combined a 10-week LCKD with an 8-week forced treadmill running program to determine whether training in conjunction with LCKD enhanced fatty acid oxidation capacity, as well as whether the maximal exercise capacity would be affected by an LCKD or training in a mice model. We found that the lipid pool and fatty acid oxidation capacity were both enhanced following the 10-week LCKD. Further, key fatty acid oxidation related genes were upregulated. In contrast, the 8-week training regimen had no effect on fatty acid and ketone body oxidation. Key genes involved in carbohydrate utilization were downregulated in the LCKD groups. However, the improved fatty acid oxidation capacity did not translate into an enhanced maximal exercise capacity. In summary, while favoring the fatty acid oxidation system, an LCKD, alone or combined with training, had no beneficial effects in our intensive exercise-evaluation model. Therefore, an LCKD may be promising to improve endurance in low- to moderate-intensity exercise, and may not be an optimal choice for those partaking in high-intensity exercise.">
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<meta name="dc.title" content="A Low-Carbohydrate Ketogenic Diet and Treadmill Training Enhanced Fatty Acid Oxidation Capacity but Did Not Enhance Maximal Exercise Capacity in Mice">
<meta name="dc.creator" content="Sihui Ma">
<meta name="dc.creator" content="Jiao Yang">
<meta name="dc.creator" content="Takaki Tominaga">
<meta name="dc.creator" content="Chunhong Liu">
<meta name="dc.creator" content="Katsuhiko Suzuki">
<meta name="dc.type" content="Article">
<meta name="dc.source" content="Ecology & Bioinformatics 2021, Vol. 13, Page 611">
<meta name="dc.date" content="2021-02-13">
<meta name="dc.identifier" content="10.3390/nu13020611">
<meta name="dc.publisher" content="Multidisciplinary Digital Publishing Institute">
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<meta name="dc.description" content="The low-carbohydrate ketogenic diet (LCKD) is a dietary approach characterized by the intake of high amounts of fat, a balanced amount of protein, and low carbohydrates, which is insufficient for metabolic demands. Previous studies have shown that an LCKD alone may contribute to fatty acid oxidation capacity, along with endurance. In the present study, we combined a 10-week LCKD with an 8-week forced treadmill running program to determine whether training in conjunction with LCKD enhanced fatty acid oxidation capacity, as well as whether the maximal exercise capacity would be affected by an LCKD or training in a mice model. We found that the lipid pool and fatty acid oxidation capacity were both enhanced following the 10-week LCKD. Further, key fatty acid oxidation related genes were upregulated. In contrast, the 8-week training regimen had no effect on fatty acid and ketone body oxidation. Key genes involved in carbohydrate utilization were downregulated in the LCKD groups. However, the improved fatty acid oxidation capacity did not translate into an enhanced maximal exercise capacity. In summary, while favoring the fatty acid oxidation system, an LCKD, alone or combined with training, had no beneficial effects in our intensive exercise-evaluation model. Therefore, an LCKD may be promising to improve endurance in low- to moderate-intensity exercise, and may not be an optimal choice for those partaking in high-intensity exercise.">
<meta name="dc.subject" content="ketogenic diet">
<meta name="dc.subject" content="exercise capacity">
<meta name="dc.subject" content="fatty acid oxidation">
<meta name="dc.subject" content="low-carbohydrate diet">
<meta name="prism.publicationName" content="Ecology & Bioinformatics">
<meta name="prism.publicationDate" content="2021-02-13">
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<meta name="prism.section" content="Article">
<meta name="prism.startingPage" content="611">
<meta name="citation_journal_title" content="Ecology & Bioinformatics">
<meta name="citation_publisher" content="Multidisciplinary Digital Publishing Institute">
<meta name="citation_title" content="A Low-Carbohydrate Ketogenic Diet and Treadmill Training Enhanced Fatty Acid Oxidation Capacity but Did Not Enhance Maximal Exercise Capacity in Mice">
<meta name="citation_publication_date" content="2021/2">
<meta name="citation_online_date" content="2021/02/13">
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<meta name="citation_firstpage" content="611">
<meta name="citation_author" content="Ma, Sihui">
<meta name="citation_author" content="Yang, Jiao">
<meta name="citation_author" content="Tominaga, Takaki">
<meta name="citation_author" content="Liu, Chunhong">
<meta name="citation_author" content="Suzuki, Katsuhiko">
<meta name="citation_doi" content="10.3390/nu13020611">
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<meta property="og:title" content="A Low-Carbohydrate Ketogenic Diet and Treadmill Training Enhanced Fatty Acid Oxidation Capacity but Did Not Enhance Maximal Exercise Capacity in Mice" />
<meta property="og:description" content="The low-carbohydrate ketogenic diet (LCKD) is a dietary approach characterized by the intake of high amounts of fat, a balanced amount of protein, and low carbohydrates, which is insufficient for metabolic demands. Previous studies have shown that an LCKD alone may contribute to fatty acid oxidation capacity, along with endurance. In the present study, we combined a 10-week LCKD with an 8-week forced treadmill running program to determine whether training in conjunction with LCKD enhanced fatty acid oxidation capacity, as well as whether the maximal exercise capacity would be affected by an LCKD or training in a mice model. We found that the lipid pool and fatty acid oxidation capacity were both enhanced following the 10-week LCKD. Further, key fatty acid oxidation related genes were upregulated. In contrast, the 8-week training regimen had no effect on fatty acid and ketone body oxidation. Key genes involved in carbohydrate utilization were downregulated in the LCKD groups. However, the improved fatty acid oxidation capacity did not translate into an enhanced maximal exercise capacity. In summary, while favoring the fatty acid oxidation system, an LCKD, alone or combined with training, had no beneficial effects in our intensive exercise-evaluation model. Therefore, an LCKD may be promising to improve endurance in low- to moderate-intensity exercise, and may not be an optimal choice for those partaking in high-intensity exercise." />
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Evaluating predictive models of species’ distributions: criteria for selecting optimal models </h1>
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by Robert P. Anderson<sup>1,2</sup>, Daniel Lew<sup>3</sup>,  A. Townsend Peterson<sup>2</sup>
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<div class="affiliation-name ">Division of Vertebrate Zoology (Mammalogy), American Museum of Natural History, New York, USA</div>
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<div class="affiliation-item"><sup>2</sup></div>
<div class="affiliation-name ">Natural History Museum & Biodiversity Research Center and Department of Ecology & Evolutionary Biology, University of Kansas, Lawrence, USA</div>
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<div class="affiliation-item"><sup>3</sup></div>
<div class="affiliation-name ">Museo de Historia Natural La Salle, Fundación La Salle, Caracas, Venezuela</div>
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<em>Ecology &amp; Bioinformatics</em> <strong>2003</strong>, <em>1</em>(1), 1; Citation times: 9738
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Received: 21 November 2001 / Revised: 12 August 2002 / Accepted: 4 September 2002 / Published: 4 January 2003
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The Genetic Algorithm for Rule-Set Prediction (GARP) is one of several current approaches to modeling species' distributions using occurrence records and environmental data. Because of stochastic elements in the algorithm and underdetermination of the system (multiple solutions with the same value for the optimization criterion), no unique solution is produced. Furthermore, current implementations of GARP utilize only presence data—rather than both presence and absence, the more general case. Hence, variability among GARP models, which is typical of genetic algorithms, and complications in interpreting results based on asymmetrical (presence-only) input data make model selection critical. Generally, some locality records are randomly selected to build a distributional model, with others set aside to evaluate it. Here, we use intrinsic and extrinsic measures of model performance to determine whether optimal models can be identified based on objective intrinsic criteria, without resorting to an independent test data set. We modeled potential distributions of two rodents ( Heteromys anomalus and Microryzomys minutus) and one passerine bird ( Carpodacus mexicanus), creating 20 models for each species. For each model, we calculated intrinsic and extrinsic measures of omission and commission error, as well as composite indices of overall error. Although intrinsic and extrinsic composite measures of overall model performance were sometimes loosely related to each other, none was consistently associated with expert-judged model quality. In contrast, intrinsic and extrinsic measures were highly correlated for both omission and commission in the two widespread species (H. anomalus and C. mexicanus). Furthermore, a clear inverse relationship existed between omission and commission there, and the best models were consistently found at low levels of omission and moderate-to-high commission values. In contrast, all models for M. minutus showed low values of both omission and commission. Because models are based only on presene data (and not all areas are adequately sampled), the commission index reflects not only true commission error but also a component that results from undersampled areas that the species actually inhabits. We here propose an operational procedure for determining an optimal region of the omission/commission relationship and thus selecting high-quality GARP models. Our implementation of this technique for H. anomalus gave a much more reasonable estimation of the species’ potential distribution than did the original suite of models. These findings are relevant to evaluation of other distributional-modeling techniques based on presence-only data and should also be considered with other machine-learning applications modified for use with asymmetrical input data.
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<div class="art-keywords in-tab hypothesis_container"><em>Keywords: </em> Asymmetrical errors; Commission; Confusion matrix; GARP; Genetic algorithms; Omission; Range
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  This is an open access article distributed under the <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" rel="noopener noreferrer">Creative Commons Attribution License</a> which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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Anderson R P , Lew D , Peterson A T . Evaluating predictive models of species' distributions: criteria for selecting optimal models[J]. Ecological Modelling, 2003(3):211-232.
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